def get_frequency_dict(input_count_dict, sum_count): f_dict = dict() if sum_count <= 0: raise KeyError("计数总和小于等于0，无法计算频率字典。") for _ in input_count_dict.items(): f_dict[_[0]] = _[1] / sum_count return f_dict

这是一个函数，可以根据输入的计数字典和计数总和计算出每个元素的频率字典。其中，input_count_dict是一个字典，用于存储每个元素的出现次数，sum_count表示所有元素的出现次数总和。函数首先会判断sum_count是否小于等于0，如果是则抛出KeyError异常。然后，函数会遍历输入的计数字典，并将每个元素的出现次数除以总和，得到该元素的频率，最终返回一个频率字典。

相关问题

stockdata = pd.read_excel('stockdata.xlsx')#pd.read_excel读取文件 count_dict = get_count_dict(stockdata) #调用get_count_dict 函数获取频数字典count_dict count = 0 for _ in count_dict.items(): count += _[1] frequency_dict = get_frequency_dict(count_dict, count) #将count_dict输入frequency 函数计算均值

这段代码是读取一个名为stockdata.xlsx的Excel文件，然后调用get_count_dict函数获取该文件中元素的频数字典count_dict。接着，代码会遍历count_dict并统计所有元素出现的次数，存储在count变量中。最后，代码会调用get_frequency_dict函数，将count_dict和count作为参数传递，计算出每个元素的频率字典frequency_dict。这里的均值可能是指所有元素出现次数的平均值。

def get_university_vec_dict(university_info: dict, refer: dict) -> object:

As an AI language model, I cannot determine the exact implementation details of the function from the given code snippet. However, based on the function signature and the input parameters, I can make an assumption about the purpose of the function.

It seems that the function `get_university_vec_dict()` takes two input parameters - `university_info` and `refer`. `university_info` is a dictionary containing information about universities and `refer` is another dictionary containing reference information.

The function is expected to return an object, which is not specified in the signature. It is likely that the function will return a dictionary containing vectors for each university in `university_info` based on the reference information in `refer`.

The implementation details of how the vectors are calculated and what specific format the output object takes are not clear from the given code snippet.